1. Field of the Invention
The present invention relates to a method of solving magnetoencephalographic and electroencephalographic inverse problems for use with systems for measuring or diagnosing brain functions. It particularly relates to a method of solving magnetoencephalographic and electroencephalographic inverse problems that enables equivalent current dipoles of the brain to be obtained from magnetoencephalograms or electroencephalograms.
2. Description of the Prior Art
A magnetoencephalography (MEG) is an apparatus used for non-invasively measuring the biomagnetic field resulting from neural activities. A recording of these magnetic fields by an MEG is called a magnetoencephalogram. The biomagnetic field involved has a magnetic flux density of from about 10−12 T to 10−13 , which is about 100-millionth the flux density of the earth's magnetic field (0.5 ×10−4T). For this reason, Superconducting Quantum Interference Devices (SQUIDs) with sensitivity in the order of 10 −14 T to 10−15 T are used to measure the biomagnetic field in a magnetically shielded room that blocks out ambient magnetic noise.
This neural biomagnetic field is produced by an ionic current flow in the cerebral cortex that arises when the cerebral cortex is stimulated. These currents are approximated by equivalent current dipoles (ECDs). Each of these equivalent current dipoles appears as the summed equivalent of the electrical activity of clusters of several thousands to several tens of thousands of neurons. The unit of these equivalent current dipole moments is the ampere-meter, different from a magnetic dipole. A magnetic field is produced around these equivalent current dipoles. The MEG measures the sum of the magnetic fields produced by the electrical activity of these neuron clusters. A flow of distributed current to the scalp shows up as an electrical potential difference between electrodes located at two points on the scalp. An apparatus called an electroencephalography (EEG) is used to measure this difference in electrical potential.
A number of equivalent current dipoles can be found by measuring the intensity of the magnetic field in the proximity of the scalp. These are referred to as MEG inverse problems. However, solutions to MEG inverse problems cannot be uniquely determined. Adding various conditions is among methods that are being used in an attempt to narrow the number of feasible solutions. One such method uses functional magnetic resonance imaging (fMRI). A number of equivalent current dipoles can also be found by measuring the electrical potential distribution on the scalp; these are referred to as EEG inverse problems.
As in ordinary magnetic resonance imaging, fMRI utilizes mainly proton signals for the imaging. In addition to using proton densities and various relaxation times to produce contrast in the images, as in the case of ordinary MRI, fMRI also reflects physiological functions. In particular, fMRI can image changes in the brain activity of a test subject as he works out a problem. In the course of working out a problem, brain activity is accompanied by the localized changes in oxygen consumption. This gives rise to changes in the blood flow, changing the concentration of deoxyhemoglobin, which is paramagnetic, having magnetization with the opposite polarity as that of the diamagnetism of the surrounding medium. Thus, the uniformity of the magnetic field undergoes localized changes, changing the free induction decay relaxation time of the magnetic resonance signal following proton excitation. This is known as the blood oxygen level dependent (BOLD) effect. fMRI utilizes this effect for high-speed generation of images of brain slices, thereby producing images of these activity states. With a spatial resolution in the order of several millimeters, fMRI has high potential.
Reference 1 (A. Korvenoja et al., “Activation of multiple cortical areas in response to somatosensory stimulation: combined magnetoencephalographic and functional magnetic resonance imaging,” Human Brain Mapping, Vol. 8, pp. 13-27, 1999) is an example of a paper that describes combining fMRI data and MEG data and fixing the location of equivalent current dipoles at brain activation peaks obtained from the fMRI data.
Various methods have been devised for actually solving magnetoencephalogram inverse problems from the above perspective. For example, fixing the locations of equivalent current dipoles only at fMRI activation volumes, and dividing up such volumes when they are large and locating an equivalent current dipole in each subvolume, is one such solution described in Reference 2 (N. Fujimaki et al., “Fitting characteristics in MEG inverse problems with position constraint,” Journal of the Japan Biomagnetism and Biomagnetics Society, Vol. 13, No. 1, pp. 162-163, 2000 (Collected Papers of the 15th Meeting of the Japan Biomagnetism and Biomagnetics Society, May 26-27, 2000, Tsukuba)), and in Reference 3, (N. Fujimaki et al., “Simulations of anisotropic fitting characteristics in MEG inverse problems with position constraint,” NeuroImage, Vol. 11, No. 5, p. 8657, 2000 (6th International Conference on Functional Mapping of Human Brain, Jun. 12-16, 2000, San Antonio)). Reference 4 (N. Fujimaki et al., “Criteria for fitting MEG dipoles with fMRI position constraints,” Proceedings of the 12th International Conference on Biomagnetism (Aug. 13-16, 2000, Helsinki)) discusses how to place dipoles with respect to spatially extended neural sources, and how to account for crosstalk influences between neighboring dipoles. In particular, Reference 4 focused on a method of handling the dipoles within a specific distance as one. Reference 5 (T. Hayakawa at al., “Human brain activity in visual search stimuli assessed by MEG multi-dipole analysis with fMRI position constraint,” Journal of the Japan Biomagnetism and Siomagnetics Society, Vol. 14, No. 1, pp. 180-181, 2001 (Collected Papers of the 16th Meeting of the Japan Biomagnetism and Biomagnetics Society, Jun. 1-2, 2001, Koganei)) relates to time characteristics of brain activity analyzed using analysis of multiple dipoles with fMRI position constraints. Reference 6 (A. Dale, et al., “Dynamical statistical parametric mapping: combining fMRI and MEG for high-resolution imaging of cortical activity,” Neuron, Vol. 26, pp. 55-67, 2000) discusses solving the problems with respect to a large number of equivalent current dipole moments, using statistical techniques combining fMRI-based information on areas of brain activity and MEG data, taking noise into account.
These conventional methods solve magnetoencephalogram inverse problems by:                1) using fMRI to obtain information on the location of brain activity;        2) locating equivalent current dipoles at brain activity areas; and        3) aligning just the dipole moment magnitudes and orientations with the MEG data.        
For example, with respect to two neighboring dipoles described in Reference 4,                4) when the distance between the two equivalent current dipoles was either not more than a predetermined reference distance used as a criterion, or        5) when the magnitudes of the two dipole moments were simultaneously large (significantly higher than the noise level),it meant there was a high interdependence between the dipoles, and therefore there was a high possibility of crosstalk, so these were grouped (the vector sum obtained), replacing them by one dipole.        
With respect to conditions 4) and 5), if the reference distance between the dipoles is reduced to around 2 cm, there is a higher possibility that the interdependence of each will remain, so that the grouping will be inadequate. Conversely, if a distance of around 4 cm is used, that possibility decreases. However, each pair of neighboring dipoles within a distance of 4 cm is grouped so that dipoles that are separated by quite a distance would be grouped. This is called the chaining effect. Grouping with the long reference distance would group dipoles within 4 cm even when there is low crosstalk. As such, it can be foreseen that when grouping is based on the criteria of distance between dipoles and the magnitudes of two dipoles, as in the case of the above conditions 4) and 5), groups cannot be optimized.
When this was examined using examples of real data, it was found that in some cases, appropriate groupings could not be achieved only with respect to conditions 4) and 5). For example, crosstalk was strongly dependent not only on dipole position, but also on the position and moment orientation of neural current sources that produce magnetic fields in the brain. Thus, there are cases where interdependency is high, even when the criterion distance between dipoles of the above 4) is exceeded, and other cases where there is low crosstalk even within the distance.
An object of the present invention is to provide a method of solving magnetoencephalogram inverse problems that provides better optimization than conventional methods of grouping moments of equivalent current dipoles.